应用近红外可见光谱快速测量柴油十六烷值

发布时间：2018-05-25 08:05

本文选题：近红外可见光谱 + 十六烷值　；参考：《光谱学与光谱分析》2017年06期

【摘要】：快速测量十六烷值对检测柴油品质及控制炼制工艺具有重大意义。首先对采集到的381份柴油样品进行近红外可见光谱波段全光谱扫描,利用小波分析(WT)对原始数据进行去噪声处理,应用竞争性自适应重加权算法(CARS)进行特征波长选择,将CARS提取的22个特征波长输入至LS-SVM预测模型,决定系数r2为0.723,预测均方根误差RMSEP为1.878%。结果表明,使用WT-CARS变量选择算法获取光谱特征波长,结合LS-SVM建模,可以快速、准确的测量柴油中的十六烷值,为进一步实现柴油十六烷值的在线检测以及其他性能参数的快速测定奠定了基础。
[Abstract]:Rapid measurement of cetane number is of great significance for diesel oil quality detection and refining process control. First, 381 samples of diesel oil were scanned in the near infrared visible spectrum band. The original data were processed by wavelet analysis (WTT), and the characteristic wavelength was selected by competitive adaptive reweighting algorithm (CARSs). The 22 characteristic wavelengths extracted by CARS were inputted into the LS-SVM prediction model, the determination coefficient R2 was 0.723, and the root mean square error (RMSEP) of prediction was 1.878. The results show that using WT-CARS variable selection algorithm to obtain spectral characteristic wavelength and LS-SVM modeling can quickly and accurately measure the cetane number in diesel oil. It lays a foundation for further on-line detection of cetane number of diesel oil and rapid determination of other performance parameters.
【作者单位】：东华大学机械工程学院;台州学院机械工程学院;华东交通大学电气工程与自动化学院;
【基金】：国家自然科学基金项目(61565005) 江西省科技支撑项目(20161BAB202060,20161BBF60060)资助
【分类号】：O657.33;TE626.24

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